Authors:
Salim Chehida
1
;
Saddek Bensalem
1
;
Davide Conzon
2
;
Enrico Ferrera
2
and
Xu Tao
3
Affiliations:
1
CNRS, VERIMAG, University of Grenoble Alpes, Grenoble, France
;
2
IoT and Robotics Area, LINKS Foundation, Turin, Italy
;
3
Computer Science Department, University of Kentucky, U.S.A.
Keyword(s):
IoT, Architecture, Model-based Design, Interoperability, Distributed Execution, Security and Privacy, Monitoring, Resiliency, Cloud, Edge, Decentralized IoT Applications.
Abstract:
The integration of Internet of Things (IoT) for building complex and critical systems requires powerful platforms enabling to deal with multiple issues, including modeling, monitoring, control, maintaining and management of IoT applications. In this work, the authors propose a new platform based on layered architecture that integrates a set of assets for model-based development of IoT systems. This platform named BRAIN-IoT aims to meet the new challenges of IoT applications and to reduce the effort for building and managing these applications. It consists of three frameworks that allow building decentralized IoT applications with computing capacity at the edge in a computing continuum with the cloud. The modeling and validation framework is used to design, develop, and validate IoT applications logic. The distributed execution framework provides an autonomic distributed infrastructure for the dynamic deployment and execution of IoT services on a mixed cloud-edge environment. The secu
rity framework enables access control, end-to-end security and privacy of data collected using IoT devices. The BRAIN-IoT platform is mapped to a well-established IoT reference architecture and experimented on two industrial use cases.
(More)